{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "75417ef5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "97fca3e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data from all four NYC taxi files into a single data frame.\n",
    "\n",
    "filenames = ['../data/nyc_taxi_2019-01.csv', '../data/nyc_taxi_2019-07.csv',\n",
    "             '../data/nyc_taxi_2020-01.csv', '../data/nyc_taxi_2020-07.csv']\n",
    "\n",
    "all_dfs = [pd.read_csv(one_filename,\n",
    "           usecols=['tpep_pickup_datetime', 'passenger_count', 'trip_distance',\n",
    "                    'fare_amount','extra','mta_tax','tip_amount','tolls_amount',\n",
    "                    'improvement_surcharge','total_amount','congestion_surcharge'],\n",
    "           parse_dates=['tpep_pickup_datetime'])\n",
    "           for one_filename in filenames]\n",
    "\n",
    "df = pd.concat(all_dfs)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d1dbaac0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21183631, 11)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "361900dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tpep_pickup_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>extra</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>improvement_surcharge</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>congestion_surcharge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-01 00:46:40</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>9.95</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-01 00:59:47</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>16.30</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-12-21 13:48:30</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>5.80</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-11-28 15:52:25</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>7.55</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-11-28 15:56:57</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>55.55</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  tpep_pickup_datetime  passenger_count  trip_distance  fare_amount  extra  \\\n",
       "0  2019-01-01 00:46:40              1.0            1.5          7.0    0.5   \n",
       "1  2019-01-01 00:59:47              1.0            2.6         14.0    0.5   \n",
       "2  2018-12-21 13:48:30              3.0            0.0          4.5    0.5   \n",
       "3  2018-11-28 15:52:25              5.0            0.0          3.5    0.5   \n",
       "4  2018-11-28 15:56:57              5.0            0.0         52.0    0.0   \n",
       "\n",
       "   mta_tax  tip_amount  tolls_amount  improvement_surcharge  total_amount  \\\n",
       "0      0.5        1.65           0.0                    0.3          9.95   \n",
       "1      0.5        1.00           0.0                    0.3         16.30   \n",
       "2      0.5        0.00           0.0                    0.3          5.80   \n",
       "3      0.5        0.00           0.0                    0.3          7.55   \n",
       "4      0.5        0.00           0.0                    0.3         55.55   \n",
       "\n",
       "   congestion_surcharge  \n",
       "0                   NaN  \n",
       "1                   NaN  \n",
       "2                   NaN  \n",
       "3                   NaN  \n",
       "4                   NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "44b9b60f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot showing total amount paid in taxi rides, per month + year\n",
    "\n",
    "p = (\n",
    "    df\n",
    "    .groupby([df['tpep_pickup_datetime'].dt.year, \n",
    "              df['tpep_pickup_datetime'].dt.month])\n",
    "    ['total_amount'].sum()\n",
    "    .plot.bar(figsize=(10,10))\n",
    ")\n",
    "\n",
    "f = p.get_figure()\n",
    "f.savefig('../../media/CH10_F11_LERNER.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c95b2a2f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a bar plot that shows how many rides there were in each month and year of our data set.\n",
    "# It's fine if there are \"holes\" in the bar plot.\n",
    "\n",
    "p = (\n",
    "    df\n",
    "    .groupby([df['tpep_pickup_datetime'].dt.year, \n",
    "              df['tpep_pickup_datetime'].dt.month])\n",
    "    ['passenger_count'].count()\n",
    "    .plot.bar(figsize=(10,10))\n",
    ")\n",
    "\n",
    "f = p.get_figure()\n",
    "f.savefig('../../media/CH10_F12_LERNER.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1d5c2d59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot showing fare_amount, extra, mta_tax, tip_amount, and tolls_amount \n",
    "# paid in taxi rides, per month + year, stacked\n",
    "\n",
    "p = (\n",
    "    df.groupby([df['tpep_pickup_datetime'].dt.year, \n",
    "                df['tpep_pickup_datetime'].dt.month])\n",
    "    [['fare_amount','extra','mta_tax','tip_amount','tolls_amount']].sum()\n",
    "    .plot.bar(stacked=True, figsize=(10,10))\n",
    ")\n",
    "\n",
    "f = p.get_figure()\n",
    "f.savefig('../../media/CH10_F13_LERNER.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "50efc4e8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot showing fare_amount, extra, mta_tax, tip_amount, and tolls_amount \n",
    "# paid in taxi rides, per number of passengers, stacked\n",
    "\n",
    "p = (\n",
    "    df\n",
    "    .groupby(df['passenger_count'])\n",
    "    [['fare_amount','extra','mta_tax',\n",
    "      'tip_amount','tolls_amount']].sum()\n",
    "    .plot.bar(stacked=True, figsize=(10,10))\n",
    ")\n",
    "\n",
    "f = p.get_figure()\n",
    "f.savefig('../../media/CH10_F14_LERNER.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cf7ae0c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a histogram showing the frequency of each tipping percentage\n",
    "# (calculating tip_amount / total_fare) \n",
    "# where the percentage is between 0% and 50%\n",
    "\n",
    "df = df[df['fare_amount'] > 0]\n",
    "df['tip_percentage'] = df['tip_amount'] / df['fare_amount']\n",
    "p = df.loc[df['tip_percentage'] <= .50, 'tip_percentage'].plot.hist()\n",
    "f = p.get_figure()\n",
    "f.savefig('../../media/CH10_F15_LERNER.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f1472b21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = (\n",
    "    df\n",
    "    .loc[lambda df_: df_['fare_amount'] > 0]\n",
    "    .assign(tip_percentage = lambda df_: df_['tip_amount'] / df_['fare_amount'])\n",
    "    .loc[lambda df_: df_['tip_percentage'] <= 0.5, \n",
    "         'tip_percentage']\n",
    "    .plot.hist()\n",
    ")\n",
    "    \n",
    "f = p.get_figure()\n",
    "f.savefig('../../media/CH10_F15_LERNER.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37aefdf0-08e0-457d-ab6e-74bcecf5ad6e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
